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Application of low-cost UASs and digital photogrammetry for high-resolution snow depth mapping in the Arctic


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Cimoli, E ORCID: 0000-0001-7964-2716, Marcer, M, Vandecrux, B, Boggild, CE, Williams, GD ORCID: 0000-0003-1769-8356 and Simonsen, SB 2017 , 'Application of low-cost UASs and digital photogrammetry for high-resolution snow depth mapping in the Arctic' , Remote Sensing, vol. 9, no. 11 , pp. 1-29 , doi: 10.3390/rs9111144.

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The repeat acquisition of high-resolution snow depth measurements has important research and civil applications in the Arctic. Currently the surveying methods for capturing the high spatial and temporal variability of the snowpack are expensive, in particular for small areal extents. An alternative methodology based on Unmanned Aerial Systems (UASs) and digital photogrammetry was tested over varying surveying conditions in the Arctic employing two diverse and low-cost UAS-camera combinations (500 and 1700 USD, respectively). Six areas, two in Svalbard and four in Greenland, were mapped covering from 1386 to 38,410 m2. The sites presented diverse snow surface types, underlying topography and light conditions in order to test the method under potentially limiting conditions. The resulting snow depth maps achieved spatial resolutions between 0.06 and 0.09 m. The average difference between UAS-estimated and measured snow depth, checked with conventional snow probing, ranged from 0.015 to 0.16 m. The impact of image pre-processing was explored, improving point cloud density and accuracy for different image qualities and snow/light conditions. Our UAS photogrammetry results are expected to be scalable to larger areal extents. While further validation is needed, with the inclusion of extra validation points, the study showcases the potential of this cost-effective methodology for high-resolution monitoring of snow dynamics in the Arctic and beyond.

Item Type: Article
Authors/Creators:Cimoli, E and Marcer, M and Vandecrux, B and Boggild, CE and Williams, GD and Simonsen, SB
Keywords: snow, snow mapping, snow depth, Arctic, remote sensing, UAS, digital photogrammetry, structure from motion
Journal or Publication Title: Remote Sensing
Publisher: M D P I AG
ISSN: 2072-4292
DOI / ID Number: 10.3390/rs9111144
Copyright Information:

Copyright 2017 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

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